The present invention relates to an apparatus and method for generating a fully focused image and, more particularly, to an apparatus and method for generating a fully focused image by using a camera equipped with a multi-color filter aperture.
Demand for digital auto-focusing techniques is rapidly increasing in many visual applications, such as camcorders, digital cameras, and video surveillance systems. Conventional cameras have come a long way in dealing with problems associated with focal settings and blur. Even though several steps have been taken, focal blur caused by varying distance of the object from the lens has been something that the conventional cameras still have to deal with. With focus set at near, mid or far regions of the scene, the captured image tends to have only that particular region in focus where as the remaining regions tend to be in out-of-focus. To solve this problem, post-processing steps in the form of blur restoration and multiple image fusion have been proposed to deal with the focusing problem.
Recently computational cameras have been developed that are capable of capturing additional information from the scene which when combined with post-processing can overcome several drawbacks of the imaging applications including: refocusing, increased dynamic range, depth-guided editing, variable lighting and reflectance, and so on.
The idea of using a multiple aperture lens has been previously proposed using micro lens array and wave front coding. However, the quality of images obtained by these optical designs is fundamentally inferior to a camera system with a large single lens. And, the resolution of these small lens arrays is severely limited by diffraction. More recent methods include single-lens multi-view image capture. This multiple filter aperture (FA) model uses parallax cues instead of defocus cues and requires only color filters as additional optical elements to the lens without requiring multiple exposures.
Meanwhile, extensive work has been done using fusion and restoration-based methods for removal of out-of-focus blur in images. Fusion algorithms using DCT, pyramids, and wavelets have been proposed to name a few where as restoration algorithms include blind de-convolution with no priori information as well as with PSF estimation.
Also, depth map algorithms have been extensively applied to stereo vision where the disparity estimate is computed as a correspondence measure through camera displacement. Shape from focus can also estimate depth from a sequence of images taken by a single camera at different focus levels. Shape from focus methods employ spatial criteria including gray level variance (GLV), sum modified Laplacian (SML), Tanenbaum, mean method, curvature focal measure, and so forth.